DocumentCode
3252416
Title
Compumetric forecasting of crude oil prices
Author
Kaboudan, M.A.
Author_Institution
MS&IS, Fogelsville, PA, USA
Volume
1
fYear
2001
fDate
2001
Firstpage
283
Abstract
This paper contains short term monthly forecasts of crude oil prices using compumetric methods. Compumetric forecasting methods are ones that use computers to identify the underlying model that produces the forecast. Typically, forecasting models are designed or specified by humans rather than machines. Compumetric methods are applied to determine whether models they provide produce reliable forecasts. Forecasts produced by two compumetric methods-genetic programming and artificial neural networks-are compared and evaluated relative to a random walk type of prediction. The results suggest that genetic programming has advantage over random walk predictions while the neural network forecast proved inferior
Keywords
commodity trading; forecasting theory; neural nets; compumetric forecasting; crude oil prices; forecasting models; monthly forecasts; random walk type; Artificial neural networks; Demand forecasting; Econometrics; Economic forecasting; Genetic programming; Load forecasting; Petroleum; Predictive models; US Department of Energy; Weather forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
Conference_Location
Seoul
Print_ISBN
0-7803-6657-3
Type
conf
DOI
10.1109/CEC.2001.934402
Filename
934402
Link To Document